西安电子科技大学学报（自然科学版）2016，Vol.43Issue(2)：1-5,28,6.DOI:10.3969/j.issn.1001-2400.2016.02.001
支撑驱动的非凸压缩感知恢复算法
Support driven recovery algorithm for non-convex compressed sensing
摘要
Abstract
A novel method is presented for the purpose of recovering sparse high dimensional signals from few linear measurements, especially in the noisy case. The proposed method works in the following two steps: The support of signal is approximately identified via Thresholded Basis Pursuit (TBP), the weighting matrix and parameters needed for the next step are also computed; The Iteratively Reweighted Lp Minimization (IRLp) procedure is used to solve the non-convex objective function. As theoretic interpretation and simulation results show, lower computational complexity is required for the proposed Support Driven IRLp(SD_IRLp) algorithm for high probability recovery, in comparison to 7 analogous methods(including an oracle estimator).关键词
压缩感知/基追踪/迭代重加权最小p范数Key words
compressed sensing/basis pursuit/iteratively reweighted Lp minimization分类
信息技术与安全科学引用本文复制引用
王峰,向新,易克初,熊磊..支撑驱动的非凸压缩感知恢复算法[J].西安电子科技大学学报（自然科学版）,2016,43(2):1-5,28,6.基金项目
国家自然科学基金资助项目(61379104) （61379104）
陕西省自然科学基金资助项目(2014JM2-6106) （2014JM2-6106）
